Pool Based Scheduling and Inventory for Service in Complex Systems

The present paper proposes a methodology based on integration of optimisation and simulation for supporting the service of complex systems, such as power plants. The proposed system is focused on pool management by using simulation as framework for testing solution proposed by an intelligent optimiser able to investigate alternative solutions. The research aim to present the bene!ts of the integrated use of modelling and simulation and AI (Arti!cial Intelligence) techniques for optimising schedule and inventory; the paper includes the experimental results obtained by the model LAPIS (Lapis Advanced Pooling Intelligent optimiser and Simulator) developed by authors to support decisions making in power plants service. The Pooling Strategies for managing a set of complex systems, such as power plants involving combined cycles (Gas Turbine, Steam Turbine and related Generators), it is an innovative approach in de!ning criteria for serving the sites by clustering the machine in subsets able to guarantee timeframes compatible with time cycle for each item for optimising availability, costs and technical commercial constraints. Therefore in real problems the stochastic factors (i.e. spare part lead times and consumption, failures, inspection duration, etc) as well as the complex processes (i.e. component refurbishment, supply expediting procedures) requires decision support systems (DSS) and the use of stochastic simulation in joint combination with intelligent optimisation represent an innovative approach. The proposed approach allows to optimise the inventory as well as the service schedule considering both quality (i.e. availability, service time) and costs; in the proposed case study the di"erent contract elements (i.e. plant stop penalties, contract duration, terms for inventory reuse) in addition to technical constraints (i.e. intervals for inspections and revisions), require a complex model for the optimisation. The paper proposes the LAPIS model description and general architecture as well as the methodology for the joint optimisation/simulation, in addition the case study on the power plant pool service is used as validation example and experimental results are proposed.